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WRF bias and sensitivity to PBL scheme over annual cycle

The seasonal dependence of Weather Research and Forecasting (WRF) model surface temperature biases and sensitivity to PBL schemes are jointly explored. For this purpose, the year 2001 was simulated using three different PBL schemes in a domain covering all Europe. The simulations were
compared with gridded observations, upper air data and high-frequency station data. Seasonal and daily cycles were analysed, aiming at providing a link between long term biases and restricted case studies. The results show that the model mean bias significantly depends on the season, being warm in winter and cold in summer. The winter warm bias is related to misrepresented cold extremes, while a systematic cold bias dominates the whole temperature range in summer. Regarding PBL schemes, an overall underestimation of the entrainment is found, with the non-local YSU scheme producing systematically warmer temperatures. It is shown that the opposite seasonal biases and the systematic behaviour of the PBL schemes along the year lead to a different best-performing scheme in winter and summer. Moreover, the best-performing PBL scheme in an average sense is a result of the compensation of errors. The average summer results can be partially explained by a detailed case study. It is concluded that short term studies should be used with caution to decide on the parametrizations to be used in long term simulations.